An Analysis of Historical and Future Temperature Fluctuations over China Based on CMIP5 Simulations简

The trends and fluctuations of observed and CMIP5-simulated yearly mean surface air temperature over China were analyzed.In general,the historical simulations replicate the observed increase of temperature,but the multi-model ensemble （MME） mean does not accurately reproduce the drastic interannual fluctuations.The correlation coefficient of the MME mean with the observations over all runs and all models was 0.77,which was larger than the largest value （0.65） from any single model ensemble.The results showed that winter temperatures are increasing at a higher rate than summer temperatures,and that winter temperatures exhibit stronger interannual variations.It was also found that the models underestimate the differences between winter and summer rates.The ensemble empirical mode decomposition technique was used to obtain six intrinsic mode functions （IMFs） for the modeled temperature and observations.The periods of the first two IMFs of the MME mean were 3.2 and 7.2,which represented the cycle of 2-7-yr oscillations.The periods of the third and fourth IMFs were 14.7 and 35.2,which reflected a multi-decadal oscillation of climate change.The corresponding periods of the first four IMFs were 2.69,7.24,16.15 and 52.5 in the observed data.The models overestimate the period of low frequency oscillation of temperature,but underestimate the period of high frequency variation.The warming rates from different representative concentration pathways （RCPs） were calculated,and the results showed that the temperature will increase by approximately 0.9℃,2.4℃,3.2℃ and 6.1℃ in the next century under the RCP2.6,RCP4.5,RCP6.0 and RCP8.5 scenarios,respectively.

An analysis of historical and future temperature fluctuations over China based on CMIP5 simulations

The trends and fluctuations of observed and CMIP5-simulated yearly mean surface air temperature over China were analyzed. In general, the historical simulations replicate the observed increase of temperature, but the multi-model ensemble (MME) mean does not accurately reproduce the drastic interannual fluctuations. The correlation coefficient of the MME mean with the observations over all runs and all models was 0.77, which was larger than the largest value (0.65) from any single model ensemble. The results showed that winter temperatures are increasing at a higher rate than summer temperatures, and that winter temperatures exhibit stronger interannual variations. It was also found that the models underestimate the differences between winter and summer rates. The ensemble empirical mode decomposition technique was used to obtain six intrinsic mode functions (IMFs) for the modeled temperature and observations. The periods of the first two IMFs of the MME mean were 3.2 and 7.2, which represented the cycle of 2–7-yr oscillations. The periods of the third and fourth IMFs were 14.7 and 35.2, which reflected a multi-decadal oscillation of climate change. The corresponding periods of the first four IMFs were 2.69, 7.24, 16.15 and 52.5 in the observed data. The models overestimate the period of low frequency oscillation of temperature, but underestimate the period of high frequency variation. The warming rates from different representative concentration pathways (RCPs) were calculated, and the results showed that the temperature will increase by approximately 0.9°C, 2.4°C, 3.2°C and 6.1°C in the next century under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios, respectively.